cor2x2 {factorial2x2} | R Documentation |
Computes the hazard ratios, confidence intervals, p-values, and correlations for the overall A, simple A, and simple AB logrank statistics.
cor2x2(time, event, indA, indB, covmat)
time |
follow-up times |
event |
event indicators (0/1) |
indA |
treatment A indicators (0/1) |
indB |
treatment B indicators (0/1) |
covmat |
matrix of covariates; one row per subject. NOTE!! Factor variables must use 0/1 indicator variables |
This function computes (i) correlation between the overall A test and the simple A test (ii) correlation between the overall A test and the simple AB test (iii) correaltion between the simple A and simple AB test. The correlation estimates are derived in Lin, Gong, Gallo, et al. (Biometrics 2016).
loghrA |
overall A log hazard ratio |
seA |
standard error of the overall A log hazard ratio |
hrA |
overall A hazard ratio |
ciA |
95% confidence interval for overall A hazard ratio |
pvalA |
two-sided p-value for overall A hazard ratio |
loghra |
simple A log hazard ratio |
sea |
standard error of the simple A log hazard ratio |
hra |
simple A hazard ratio |
cia |
95% confidence interval for simple A hazard ratio |
pvala |
two-sided p-value for simple A hazard ratio |
loghrab |
simple AB log hazard ratio |
seab |
standard error of the simple AB log hazard ratio |
hrab |
simple AB hazard ratio |
ciab |
95% confidence interval for simple AB hazard ratio |
pvalab |
two-sided p-value for simple AB hazard ratio |
corAa |
correlation between the overall A and simple A test statistics |
corAab |
correlation between the overall A and simple AB test statistics |
coraab |
correlation between the simple A and simple AB test statistics |
Lin, D.Y., Glong , J., Gallo, P., Bunn, P.H., Couper, D. Simultaneous inference on treatment effects in survival studies with factorial designs. Biometrics, 2016; 72: 1078-1085.
# First load the simulated data variables. The "simdat" file is # a 100-by-9 matrix which is loaded with the factorial2x2 package. time <- simdat[, "time"] event <- simdat[, "event"] indA <- simdat[, "indA"] indB <- simdat[, "indB"] covmat <- simdat[, 6:10] cor2x2(time, event, indA, indB, covmat) # $loghrA # [1] 0.05613844 # $seA # [1] 0.4531521 # $hrA # [1] 1.057744 # $ciA # [1] 0.4351608 2.5710556 # $pvalA # [1] 0.9014069 # $loghra # [1] 0.1987329 # $sea # [1] 0.6805458 # $hra # [1] 1.219856 # $cia # [1] 0.3213781 4.6302116 # $pvala # [1] 0.7702714 # $loghrab # [1] 0.2864932 # $seab # [1] 0.6762458 # $hrab # [1] 1.331749 # $ciab # [1] 0.3538265 5.0125010 # $pvalab # [1] 0.6718193 # $corAa # [1] 0.6123399 # $corAab # [1] 0.5675396 # $coraab # [1] 0.4642737